Applied & Human-Centered · Computer Science & AI
Social & Information Networks
The newest papers in Social & Information Networks that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
172 papers, from 4 September 2026 to 5 November 2026: 172 arXiv preprints.
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Newest papers, page 9
A Multi-Stage Agentic Framework for Effective Counter-Narrative Generation and Refinement
The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen polarization, fuel public distrusts, and…Exact Community Recovery in Bipartite Networks
Community detection in bipartite networks is a fundamental problem in modern data analysis, with applications in recommendation systems, biological networks, and social network analysis.Same Day, Same Story; One Day Ahead, a Different Signal: The Dual Validity of Financial Sentiment
Financial NLP has a standard workflow: validate a sentiment tool against human labels, then trust it to extract market signal.Automated Identification of Competing Narratives in Political Discourse on Social Media
Social media platforms have become central to shaping political discourse, serving as arenas where narratives form and evolve, influencing public opinion.Learning structural balance of graphs from quantum spectral features
We develop a quantum approach to spectral feature extraction from the density of states (DOS) of a problem-dependent Hamiltonian, and apply it to machine learning on signed graphs.Motifs in temporal hypergraphs
Network motifs, recurrent local patterns of interactions in graphs, provide fundamental insights on the interplay between structure and functionality in complex systems.How neighbourhood ideology shapes misinformation belief in densely tied social networks
With the rapid spread of news on social media, understanding the propagation of misinformation is becoming increasingly important.SynCo: Synthetic Community-Aware Attributed Graph Generator for Graph Neural Network Benchmarking
Graph Neural Networks (GNNs) are powerful models for handling attributed graphs in tasks such as classification, link prediction, and community detection, as they enable the aggregation of…Topology-induced Operators Reveal Complementary Graph Representations without Training
Graph representation learning has largely focused on designing increasingly sophisticated models to transform graph topology into vector representations, or embeddings.LLMs for Social Network Modeling: From Network Generation to Dynamic Processes
Large language models (LLMs) are rapidly emerging as a new paradigm for modeling social networks by representing users and their relationships and interactions through natural language.Polarity-Asymmetric Structural Calibration for Link Sign Prediction
Link sign prediction (LSP) aims to infer the positive or negative polarity of unobserved links in signed networks.WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societies
Safety evaluations typically focus on individual agents, but interacting agents can spread harmful information and influence the environment in which later decisions are made.